Knowledge Perspective of IT Project - Example

Review of Modeling the Knowledge Perspective of IT Project Article Name Institution Date Introduction Information technology projects usually facilitate organizational change. Thus, successful implementation of an IT-enabled change is vital for organizational success. The knowledge perspective of IT projects views projects as places where knowledge and learning is paramount. In this perspective, projects act as channels for the knowledge that enters through methodologies, people, and prior knowledge. During a project, knowledge should be created, transferred, exploited ad integrated so as to generate new organizational value. This focus on knowledge gives way to new insights since IT projects are mainly knowledge work. Additionally, modern day IT projects are usually more about the incorporation of rather than construction of software. Knowledge management in IT projects is the application of processes ad principles designed to make pertinent knowledge accessible to project team. The paper seeks to affirm that effective management of knowledge enhances the development and incorporation of knowledge, reduces knowledge loss and fills up knowledge gaps all through the period of the project. A knowledge-based view of IT projects According to Reich, (2007), and Reich, Gemino & Sauer (2008), numerous IT projects are knowledge based, implying that their success is dependent upon the effective development, consumption and transfer of knowledge. However, it is astonishing that aspects of knowledge management have not been appropriately incorporated into typical IT project management. For instance, project managers identify the requirement to document the lessons learned and usually do so, but the learning are infrequently incorporated into the project knowledge of the organization. Kinds of knowledge that need to be managed in IT projects The two important types of knowledge that need to be managed in IT projects are the process knowledge and the domain knowledge. Process knowledge refers to the knowledge that team sponsors and team members have on the project methodology, structure, time frames and tasks. It is significant from the viewpoint of recognizing diverse roles in a project and what is anticipated from them. A universal recognition of knowledge also empowers members of the team to systematize themselves in good way to attain the project goals (Reich, 2007; Reich, Gemino & Sauer, 2008). According to Reich, (2007), domain knowledge is the product, technical ad business knowledge pertinent to a project. Typically, domain knowledge is communally held by a huge number of persons. It is the role of a project manager to make sure that individuals who possess this knowledge are recognized and consulted at suitable times. Domain knowledge is widely spread outside and within project team and project sponsor are the most informed on the industry and the opportunity or problem being addressed. Technical expects outside and inside the organization have knowledge on the technologies that can be used in the project wile project members have deep knowledge on the business together with its business processes( Reich, Gemino & Sauer 2008). There are also two in forms of knowledge that are important in IT projects; institutional knowledge and cultural knowledge. Institutional knowledge is a blend of a company’s power structure, values, politics and history ad it is transferred through anecdotes or stories by organizational observers ad insiders. The project team is supposed to have a superior awareness of this knowledge so as to get work done and it is especially significant for persons who are drafted into a project from outside the company. Cultural knowledge refers to discipline based cultures, such as academic, IT and business and national cultures. Ajmal (2006) argues e people managing the project require that kind of knowledge so as to lead teams which are made up of people from different cultures and disciplines. Team members within interdisciplinary projects should be aware of differences in work cultures amid diverse disciplines. Additionally, project teams are usually composed of individuals from diverse nations, thus the need for the awareness of norms of diverse national cultures (Reich, 2004; Reich, Gemino & Sauer, 2008). Components of knowledge-Based risks in IT projects Knowledge inputs Reich, Gemino & Sauer (2008) argue that there are two major knowledge risks at the start of a project: the failure of team members to learn from previous projects and failure to meet the knowledge needs of the project during selection of team. When the team fails to access lessons learned from similar projects, it will lack significant institutional or domain knowledge but if this knowledge is available to the project, it will influence the process of emergent knowledge and shape the way project managers monitors and plans the project. According to Reich (2007), lessons not learned are the most identified knowledge based risk. Though numerous companies insist on proper documentation of lessons learned at end of a project, few utilize it effectively on consequent projects. This is because project management and teams are pressured or keen to get on proper working of the project and taking time to read and reflect upon documentation from precedent projects is considered a waste of time. Getting the appropriate team members is significant because the project manager requires all pertinent knowledge regions to be included in the team or accessible to team when they require it. When a flaw occurs in the team selection procedure, the project manager is not able to identify what the team collectively knows, or more significantly, what the team doesn’t know. Riech (2004) argues that the project major precisely requires individuals who possess the required cultural, institutional and domain knowledge. Usually, however, project managers have minute or o control on selection of team. On the contrary, even if the project managers participate in selection of team, it might be difficult to recognize the skills required upfront (Reich 2007; Reich, Gemino & Sauer 2008). Project Governance Project governance is the obligation of numerous key positions, including executive, project steering committee, project manager, project champion, and project sponsor. From the knowledge viewpoint, process governance entails role understanding and volatility. Volatility risk in project governance is the loss of a member of governance structure who influences or controls project direction and resources. The removal of a project manager or other executive from the project is performed for strategic motives but it leads to significant domain, process and institutional knowledge losses which might make targets to be unaccomplished or gains to go unidentified. Another risk in project governance is the lack of role knowledge by the governance team: project manager and sponsor (Reich, Gemino & Sauer, 2008). Project sponsor supporting a project for the first time might not be aware of when to offer support to the project and when to stiffen the rein. They might also fail to distinguish between projects issues that are staid and project issues that are easily addressed. Reich (2007) notes that though companies identify and act on need to train managers so as to equip them with knowledge required to do their tasks, very few accord this same attention to the project sponsors. As a consequence, numerous project managers recognize that they have to lightly educate their sponsors concerning what requires to be performed so as to propel thing ahead in hard times. Project operational processes According to Reich, Gemino and Sauer (2008), there are five knowledge risks in the major body of IT projects: knowledge integration, loss of the team members, knowledge transfer, and knowledge loss amid phases and deficiency of a knowledge map. Knowledge integration refers to the procedure of bring together diverse specialist types of knowledge, for instance, technical, domain and business knowledge so as to address a recognized project issue and to develop knowledge that is superior than the amount of its parts. Poor decisions may occur when specialist not fails to be integrated. For instance, a technical specialist who is undertaking configuration of an enterprise system might not clearly understand the way a business process functions. It is vital for domain knowledge transfer from the consultant or vendor to the interior projects in a project that is executing a new hardware or packaged software. Reich (2004) argues that inadequate integration of diverse forms of knowledge is a key risk on big projects which engage specialist knowledge from diverse domains. Apart from the complexity in elucidating the internal functioning of technology, there are numerous agency problems innate in project governance processes. When major members of team get out of the project, there is knowledge loss. Even though project managers theoretically recognize that losing major team members leads to knowledge gaps, they usually fail to develop a plan for mitigating such losses. Team members and project managers make a huge amount of correlated decisions. The more complex the domain difficulties, the more significant for team members to have a knowledge map, showing knowledge edge in the team and knowledge that is available to team members, which enhances them to effectively and efficiently address intricate problems. Lack of a knowledge map makes it impossible for each individual a team to know everything relating to a project, even at a greater level. Research studies have revealed that knowledge maps and networks that emerge by interactions amid team members are highly effective than focusing upon knowledge integration (Reich, 2007; Reich, Gemino & Sauer 2008). Knowledge is lost between phases as a result of changes in team composition. Since team composition usually changes one phase to another in IT projects, there is a considerable risk because domain knowledge created by one phase will not be adequately passed on to the consecutive phase. This difficulty is aggravated in long projects and in implicit project teams. According to Reich, (2004), knowledge loss between phases can be addressed through proper documentation, but not everything can be communicated via the written word. A conversation with an expert is a more useful way than reading a written document. Conversations in which an individual can go back and forth, discussing and elucidating the validation behind particular decisions are the best means of transferring knowledge across phases. Project outputs The knowledge risk at the termination of a project is that the lessons learned are inadequately captured. A partial debriefing during and at end of the project makes team members to have a splintered of what they have learned and reasons as to why things went right or wrong during the project. Failure of project managers to capture learned lessons, they hider team level learning and obstruct opportunities for the improvement of organization competency I management and completion of projects (Reich, Gemino & Sauer, 2008). Modeling project performance using a knowledge lens There is no model that completely integrates both the action and knowledge perspectives of IT projects and trials to expain or predicts the variances in project performance. However, Gemino, Reich, and Sauer (2008) proposed and tested a temporal model of information technology project performance (TMMP). They argue that it is significant to separate risk factors as prior and emergent risk factors. Additionally, a priori risk factors may have a direct impact on emergent risk factors. Efficient delivery of anticipated performance form IT projects remains a vital challenge for numerous companies. An improvement in the understanding of the way several factors affect project performance is thus a vital research objective. Their study revealed that performance may be better recognized through detaching risk factors into earlier or a prior risk factors and later or emergent risk factors, and then modeling the impact of the former on the later. According to Gemino et al (2008) project performance, which is the dependent variable, is measured through considering both process (schedule and budget) and product (outcome) constituents. The temporal model entails interactions amid project management practices, project performance components and risk factors. The model is tested utilizing partial least square analysis with data study of 194 projects managers. The results show that the TMPP increases the explanatory power when compared to models that connect risk factors directly to the project performance. The outcomes display the significance for active risk management for identifying, planning for, as well as managing emergent or a priori risk factors. According to Ajmal (2006), the discovery of a strong relation amid structural risk factors and consequent volatility depicts the need for the risk management practices to identify the interrelation of emergent and a priori risk factors. The outcomes confirm the significance of organizational support, project management practices and knowledge resources, and demonstrate the manners in which they support each other (Gemino et al, 2008). According to Reich, Gemino and Sauer (2008), in the temporal model performance of IT project, the resources and risks in the project are modeled over time. These time elements are T-1 which is the time before the start of the project, T-2 which is the time during which a project is undertaken ad T-3 which is the time at the end of a project. The structural risks of a project (duration, budget, size, technical complexity and schedule) and knowledge resources connected with the project (knowledge of executive sponsor, team, project manager and project client and uncertainty involving requirements are modeled are T-1. Thus, T-1 functions to separate knowledge resources from other risks. There are three constructs of importance at T-2: Project management practices, volatility risk and organizational support resources. These construct s have elements from both the knowledge and action perspectives. The organizational support resources construct is extracted from a wholesome action perspective and it gauges the commitment and support behaviors of client managers and executive sponsor. The project management practices construct is concerned with the administrative activities of project manager (use of tools and methodologies), process integration (with users and within teams) and expertise coordination (knowledge sharing and knowledge mapping). Volatility risk encompasses three sub-constructs: project target change such as changes in scope schedule or budget; exogenous change, such as changes in company strategy and industry; and knowledge loss, such as loss of executive sponsor or project manager. The two aspects of project performance at T-3 are product performance (organizational quality and benefits) and process performance (schedule attainment and budget). There is no any knowledge output overtly contained in T-3 model (Reich, Gemino & Sauer, 2008). Influence of Construct Level: Knowledge Resources on Temporal Model of IT Projects At T-1, the project begins with an initial allocation of knowledge resources. Higher levels of knowledge resources positively affect both project management and organizational support practices. Organizational support and project management practices positively influence one another in a form of virtuous cycle. In temporal model, project management practices directly and indirectly influence product performance, via organizational support. Through this perspective, the project manager should leverage knowledge resources in to manage the project via project management practices in order to positively affect organizational support and ultimately support both process and product performance. Thus, knowledge resources assist the project manager to take the essential actions that help the team to accomplish goals of the project. Additional, great levels of knowledge resources enhance high levels of project management and organizational support practices and thus enable organizational support to completely influence project success (Reich, Gemino & Sauer 2008). Proposed changes the temporal model of IT projects According to Reich, (2004), there are numerous changes that must be made to the temporal model it enable it completely specify the learning and knowledge risks. At T-1, elements should be added to knowledge resources construct like lessons learned and at T-2 model knowledge should be created via integration and transfer. Separation of expertise coordination from other project management practices which manage time ad tasks is required at T-2. However, this may generate overlaps amid knowledge and action activities of a project manager and obtaining a conceptual explanation might also prove to be a hard task. Reich (2004) argues that, at T-2, there is the need to add within team learning that is created when teams debrief amid phases, and examination of their assumptions at vital decision points. Other modifications to be done at T-2 include modeling to knowledge loss between phases, as well as knowledge loss as a result of loss of team members and separation of elements of volatility that tackle knowledge loss as a result of turnover of governance functions from other elements of volatility like target change and exogenous change. Reich (2004) suggests that knowledge outputs of the IT project should be added. The first step can include modeling organizational learning and individual learning as knowledge outputs (Reich, 2004). Use of five constructs to model knowledge perspective of IT projects Reich, Gemino and Sauer (2008) views the above proposed changes on the temporal model by Reich as considering knowledge risks only. They argue that this model clearly doesn’t put into consideration the effect of institutional and cultural knowledge on project success and also might be unsuccessful in capturing Client’s contribution and knowledge needs. They suggest five constructs that should be used in modeling the knowledge perspective in IT projects. The 1st construct would contain the fist level of knowledge resources accessible to the project which will be measured at T-1 via the knowledge inputs such as knowledge of project managers, team members, client manager, executive sponsor, lessons learned and knowledge networks and the knowledge gaps such as requirements of ambiguity. Knowledge resources will be anticipated to positively affect knowledge creation, because a higher knowledge level in the project will enable highly advanced measures of knowledge transfer, integration and coordination (Reich, Gemino & Sauer, 2008). Reich, Gemino and Sauer (2008) note that the second construct would characterize the knowledge lost during the T-2 phase. This may include loss of individuals such as project sponsor, team members, and project manager and further major sources of knowledge like consultants and vendors. Loss of knowledge would be anticipated to differ indirectly with creation of knowledge, as increased levels of learning may encourage people participating in the project to stay on the project, whilst significant knowledge loss may cripple or slow creation of new knowledge. Loss of knowledge would be anticipated to negatively affect both knowledge and project outcomes. The 3rd construct would characterize attempts taken by project manager together with other project leaders to develop new knowledge via transfer, coordination ad integration. Reich, Gemino and Sauer (2008) argue that this construct would also characterize the within- project learning achieved by project participants. Creation of knowledge would be anticipated to positively affect both knowledge and project outcomes. The 4th construct would contain the conventional measures of such: the achievement of organizational value (product performance) and achievement of targets (process performance). The 5th construct would model knowledge outputs of a project. At individual level, it would entail assessment of increases I domain, institutional, cultural and process knowledge stocks. At organizational level, it would entail measurement of the entire capability of the company to successfully execute projects, both through obtaining value and through attaining targets (Reich, Gemino & Sauer, 2008). Conclusion It can be concluded that Information technology projects are important because they enhance organization change and thus effective implementation of an IT- based change is critical for organizational success. The knowledge perspective of IT projects views knowledge as a paramount thing in IT projects because projects acts as channels for knowledge that enters through methodologies, prior learning and people. During the project, knowledge created, integrated, transferred and utilized to develop new organizational value. This focus on knowledge leads to new insights since IT projects are mainly knowledge work. Additionally, present day IT projects are highly based on integration of systems than o the production of software. It is therefore essential that every project manager combines numerous sources of knowledge on technologies as well as business processes in order to generate organizational value. The project manager should apply the processes and principles designed to make pertinent knowledge accessible to project team members. Effective management of knowledge IT projects will facilitate knowledge creation and integration, minimization of knowledge losses and filling up of knowledge gaps in the project. References Reich, H. B, (2007). Managing knowledge and learning in IT projects: A conceptual framework and guidelines for practices. Project management journal, 38(2), 5-7. Reich, H. B, (2004). Managing knowledge within IT projects: A review of current literature and directions for future research. Gemino, A., Reich, H., & Sauer, C., (2008). A temporal model of information technology project performance. Journal of Management Information Systems, 24(3), 9-44. Reich, H. B., Gemino, A., & Sauer, C., (2008). Modeling the knowledge perspective of IT projects. Project Management Journal, Vol. 39, no. 1. Ajmal, M. M. (2006). Managing knowledge in project-based organizations: A cultural perspective. Vaasa: University of Vaasa Read More